| Computer # |
| 4469.
 | 145 | Decorrelation Algorithm for Correcting B1 Artifacts in APTw Imaging at 3 Tesla Christos Papageorgakis1, Mauro Zucchelli1, Ottavia Dipasquale1, Laura Mancini2,3, Sotirios Bisdas2,3, Patrick Liebig4, Moritz Zaiss5, and Stefano Casagranda1
1Department of R&D Advanced Applications, Olea Medical, La Ciotat, France, 2Lysholm Department of Neuroradiology, University College of London Hospitals NHS Foundation Trust, London, United Kingdom, 3Institute of Neurology UCL, London, United Kingdom, 4Siemens Healthcare GmbH, Erlangen, Germany, 5Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany Keywords: CEST / APT / NOE, CEST & MT, CEST, APTw, B1-correction Motivation: We present a data-driven approach for B1 correction in APTw MRI eliminating the requirement for additional volume sampling at various B1-values, thereby significantly reducing acquisition time. Goal(s): This enhancement ensures feasible and robust B1 correction in clinical settings. Our method establishes homogeneity in white matter (WM) and gray matter (GM) values within 3D-APTw volume. Approach: By modeling the correlation between rB1 and the APTw data, followed by a decorrelation algorithm, we achieve closer alignment of WM and GM values across 3D volume. Results: This rapid technique considerably reduces acquisition time and significantly improves the coherence of WM and GM values throughout the slices. Impact: The proposed B1 decorrelation technique strongly impacts qualitative and semi-quantitative APTw imaging applications due to considerable reduction in B1 artifacts. Homogeneous contrast among WM, GM, and tumor values is achieved within and across slices. |
| 4470.
 | 146 | Brain Temperature Mapping Based on Chemical Exchange Saturation Transfer of Creatine at 5.0T Siqi Cai1,2, Chongxue Bie1, Yang Zhou1, Chao Zou1, Xi Xu1,2, Chunxiang Jiang1, and Lijuan Zhang1,2
1Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 2University of Chinese Academy of Science, Beijing, China Keywords: CEST / APT / NOE, Thermometry Motivation: High-resolution brain thermometry remains challenging. Goal(s): To estimate the feasibility of creatine chemical exchange saturation transfer (CrCEST) imaging for brain thermometry. Approach: The CrCEST imaging of creatine phantom and swine brain was conducted at various temperatures on a 5.0T MR scanner (UIH Jupiter). The relationship between the apparent offset of CrCEST and the temperature was estimated with regression analysis, based on which the temperature maps were generated. Results: Strong linear relationships between temperature and the apparent CrCEST offset were identified for both the creatine phantom (0.005ppm/oC) and the ex vivo swine brain (0.008ppm/oC) experiments. Impact: The linear relationship between the apparent CrCEST offset and temperature confirmed the feasibility of CrCEST for high-resolution brain thermometry. |
| 4471.
 | 147 | Accelerated CEST MRI by reconstruction using low-rank plus sparse decomposition in both k-space and image domain Chuyu Liu1, Rui Guo1, Zhongsen Li1, and Xiaolei Song1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China Keywords: CEST / APT / NOE, CEST & MT Motivation: Chemical Exchange Saturation Transfer (CEST) acceleration requires robust contrast recovery from under-sampled k-space data. Goal(s): To achieve accelerated CEST-MRI with well-preserved contrast among different tissue types. Approach: Herein we proposed a reconstruction method that iteratively decomposed both K-space and Image domains into Low-rank plus Sparse components, termed as KILS. Results: Retrospective experiments from the healthy adults and brain tumor patients indicated that KILS could achieve an 8X acceleration factor, with well-preserved contrast among different tissue types. Experiments conducted on human liver at 3T and rat brain at 9.4T demonstrated that KILS exhibited good general applicability, suggesting its potential clinical utility. Impact: We developed KILS, which utilizes an iterative low-rank plus sparse matrix
decomposition in both k-space and image
domains for robust CEST
contrast recovery from under-sampled k-space data and holds significant
potential. |
| 4472.
 | 148 | Superior HyperCEST Performance of Membrane-Anchored Xenon Hosts in Nanocarriers with Variable Membrane Fluidity Leif Schröder1,2,3, Felix Schnabel1, and Jabadurai Jayapaul1
1Translational Molecular Imaging, German Cancer Research Center, Heidelberg, Germany, 2Department for Physics and Astronomy, Ruprecht Karls University Heidelberg, Heidelberg, Germany, 3German Cancer Consortium (DKTK), Heidelberg, Germany Keywords: Contrast Agents, Contrast Agent Motivation: The efficiency of CEST agents for hyperpolarized 129Xe depends on the exchange rate of Xe in/out of tailored host structures. For liposomal designs, this may be influenced by the phospholipid membrane fluidity. Goal(s): This study investigates how cholesterol, which is often added for liposome stability, impacts the HyperCEST performance. Approach: We compared the changes in CEST buildup from liposomes with variable cholesterol content and either membrane-anchored (i.e., lipopeptide-based) or freely diffusing Xe host. Results: The HyperCEST efficiency for membrane-anchored Xe hosts is much less sensitive to membrane stiffening than for unbound hosts. Lipopeptide-based HyperCEST agents are thus a powerful approach for biosensor design. Impact: The HyperCEST performance of membrane-anchored xenon hosts in liposomal nanocarriers shows reduced
susceptibility to membrane stiffening compared to non-functionalized hosts.
These less susceptible lipopeptide-based hosts are thus the preferred approach for
future in vivo applications. |
| 4473.
 | 149 | A 3D steady-state CEST sequence for in vivo imaging of cerebral blood vessels at 3T Chuyu Liu1, Zhensen Chen2,3, Zhongsen Li1, Xubin Chai4,5, Nan Gao1, and Xiaolei Song1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, 2Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, 3Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China, 4State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China, 5Beijing Neurosurgical Institute, Capital Medical University, Beijing Tiantan Hospital, Beijing, China Keywords: CEST / APT / NOE, CEST & MT Motivation: Cerebral blood vessels play key roles in oxygen transportation and nutrition metabolism. MR angiography provides non-invasive and comprehensive information on vessel structure, blood volume and even oxygenation level. A metabolic MR imaging tool for vessels may facilitate more clinical needs. Goal(s): To observe CEST signal in vessels including proteins and peptides, sugars and macromolecule that contains aliphatic protons. Approach: We developed a 3D steady-state vessel-CEST sequence. Sequence parameters were optimized by simulation. Repeatability and difference between arteries and veins were investigated on 8 subujects. Results: Preliminary results demonstrated good repeatability of the pulse sequence, and allow sensitive visualization of blood signal in vessels. Impact: We developed a 3D steady-state CEST sequence for
in vivo z-spectra analysis of cerebral vessels.Preliminary results
demonstrated good repeatability of the sequence,and difference between arteries
and veins were observed.These facts illustrated the potential value in
diagnosis of blood metabolism-related diseases. |
| 4474.
 | 150 | One-Shot Learning for CEST-Centered Multiparametric MRI: Training Neural Network with One Single Scan Zhekai Chen1, Tao Gong2, Jianfeng Bao3, Liangjie Lin4, and Lin Chen1
1Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, School of Electronic Science and Engineering, National Model Microelectronics College, Xiamen University, Xiamen, China, 2Departments of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China, 3Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China, 4Clinical and Technical Support, Philips Healthcare, Beijing, China Keywords: CEST / APT / NOE, CEST & MT Motivation: Multiparametric imaging offers comprehensive information. However, its practical application is hindered by extended scanning times. Goal(s): To develop a CEST-centered multiparametric approach capable of producing multiple quantitative maps. Approach: ResNet was utilized to simultaneously quantify amide, NOE, MT, DS, B0, T1 and T2. By incorporating a reweighting scheme in conjunction with transfer learning, we demonstrate one single scan is adequate to train a well-performing neural network. The robustness and generalizability of the proposed method were validated using multicenter data. Results: The proposed method outperformed state-of-the-art CEST deep learning method, providing more accurate quantification results, all while requiring a limited amount of training data. Impact: The
proposed method has the potential to establish a CEST-centered multiparametric
approach, eliminating the need for multiple scanning protocols and,
consequently, reducing scan time. |
| 4475.
 | 151 | Removing lipid artifacts in CEST imaging with a two-point turbo-spin-echo Dixon method Shengxiang Huang1, Zhechuan Dai1, Junjie Wen1, Xingwang Yong1, Yi-Cheng Hsu2, and Yi Zhang1
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, 2siemens-healthineers, Shanghai, China Keywords: CEST / APT / NOE, Fat Motivation: Chemical Exchange Saturation Transfer (CEST) imaging has advanced by capturing molecular-level information of tissue metabolites. However, strong fat artifacts can affect the contrast of CEST signals. Goal(s): We aim to seek a fat suppression technique that maintains high image signal-to-noise efficiency. Approach: By combining TSE-CEST and flexible two-point Dixon methods, utilizing accurate multi-peak fat models, the obtained water-only images are used as CEST images. Results: Z-spectra and MTRasym of ROIs in the water-fat-Creatine phantoms and high-fat fraction regions near the human knee demonstrate that accurate fat suppression achieved in the CEST images. Impact: We proposed
a two-point turbo-spin-echo Dixon technique, which utilizes TSE-CEST instead of
the conventional gradient echo Dixon acquisition. Robust fat suppression was
achieved in the phantoms and human knee by utilizing Dixon on the two images
acquired for each offset. |
| 4476.
 | 152 | Accelerating CEST MRI using Data-Driven Z-Spectral Compressed Sensing Haipeng Xu1, Tao Gong2, and Lin Chen1
1Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, School of Electronic Science and Engineering, National Model Microelectronics College, Xiamen University, Xiamen, China, 2Departments of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China Keywords: CEST / APT / NOE, CEST & MT Motivation: CEST MRI requires the collection of multiple saturated images with different saturation offsets, resulting in prolonged scan times, which hinders its clinical applications. Goal(s): we aim to reduce the scan time of CEST MRI by recovering the undersampled Z-spectrum to full-sampling counterpart using data-driven Z-spectral compressed sensing method. Approach: The modified U-Net was employed for Z-spectral recovery. Training data were generated using Bloch equation. Numerical simulations and in vivo experiments on rat brains were conducted to validate the proposed method. Results: The results demonstrate that our method outperformed conventional interpolation methods, and threefold undersampling rate can be achieved without discernible degradation in quantification. Impact: The
proposed method can efficiently reduce the scan time of CEST MRI, potentially
facilitating its clinical applications. |
| 4477.
 | 153 | Simultaneous Measurement of CEST and $$$T_1$$$ using Model-based Multi-Pool-Lorentzian Look-Locker Reconstruction Markus Huemer1, Nick Scholand1, Daniel Mackner1, Clemens Stilianu1, Moritz Zaiss2,3, and Rudolf Stollberger1
1Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria, 2Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany, 3High-Field Magnetic Resonance Center, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany Keywords: CEST / APT / NOE, CEST & MT, Lorentzian, Model-based Reconstruction Motivation: Conventional quantitative CEST experiments require the additional determination of $$$T_1$$$. CEST sequences include $$$T_1$$$ relaxation periods that can be exploited to estimate $$$T_1$$$ simultaneously to the CEST parameters. Goal(s): The development of a technique for efficient simultaneous quantification of CEST contrast and $$$T_1$$$.
Approach: Integration of a FLASH acquisition train after conventional CEST saturations. Simultaneous CEST contrast and $$$T_1$$$ fitting is achieved by extending the Lorentzian model of the CEST spectrum with a Look-Locker model for the FLASH readout. Results: The proof-of-concept was implemented, and first results are demonstrated in a two pools phantom and a four pool in vivo study. Impact: The presented technique enables calculating $$$T_1$$$ corrected quantitative CEST results from one measurement. This simplifies the application of the apparent exchange-dependent relaxation ($$$MTR_{AREX}$$$), the quasi-steady-state$$$\;$$$contrast and other CEST metrics, which require a $$$T_1$$$ map, making them more accessible. |
| 4478.
 | 154 | Neural Bloch-McConnell fitting (NBMF): unsupervised test-time learning of clinical semisolid MT/CEST MRF reconstruction Alex Finkelstein1, Nikita Vladimirov1, Simon Weinmüller2, Moritz Zaiss2,3,4, and Or Perlman1,5
1Department of Biomedical Engineering, Tel Aviv University, Tel-Aviv, Israel, 2Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 3Magnetic Resonance Center, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany, 4Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 5Sagol School of Neuroscience, Tel Aviv University, Tel-Aviv, Israel Keywords: CEST / APT / NOE, Molecular Imaging, AI, Deep Learning, Unsupervised Learning, Bloch-McConnell, Differentiable Physics Motivation: MRF-based quantification of semi-solid MT/CEST proton-exchange requires a computationally demanding dictionary synthesis/matching. Recently reported unsupervised learning alternatives were incompatible with pulsed clinical CEST and multi-pool imaging. Goal(s): To develop a training-set-free MRF reconstruction method, learning directly from the acquired data via pulsed-saturation-compatible physical modeling. Approach: A differentiable multi-pool Bloch-McConnel simulator was designed and embedded within a test-time learning framework. Validation was performed using L-arginine phantoms and a human subject at 3T. Results: The method enabled quantitative MT/CEST reconstruction in ~1 minute. The resulting maps were highly correlated with ground-truth in-vitro (Pearson’s r>0.95). In-vivo, semi-solid volume fractions were in agreement with MRF-based maps (r~0.8). Impact: A one-stop-shop for semisolid MT and CEST MRF reconstruction was developed, enabling a training-set-free rapid quantification of exchange parameters on clinical scanners. This accessible approach could help a variety of Bloch-fitting applications to benefit from deep learning through differentiable spin-physics. |
| 4479.
 | 155 | Evaluating the effectiveness of distortion self-correction for CEST-EPI Jianpan Huang1,2, Se Weon Park2,3, and Kannie W. Y. Chan2,3,4,5,6
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China, 2Hong Kong Centre for Cerebro-Cardiovascular Health Engineering, Hong Kong, China, 3Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China, 4Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, 5Tung Biomedical Sciences Centre, City University of Hong Kong, Hong Kong, China, 6City University of Hong Kong Shenzhen Research Institute, Shenzhen, China Keywords: Data Processing, CEST & MT, EPI Motivation: EPI-based CEST (CEST-EPI) is fast but suffers from image distortion caused by field susceptibility. Goal(s): We aimed to evaluate the effectiveness of using the field map generated by the Z-spectra to achieve the distortion self-correction (DISC) for single-shot CEST-EPI without additional acquisition of a field map. Approach: The effectiveness of DISC strategy was demonstrated in CEST-EPI experiments of a creatine phantom and in vivo mice. CEST-RARE was used as a reference. Results: Without acquiring an additional field map, DISC retrospectively and effectively corrected geometric distortion in CEST-EPI, leading to improved SSIM and spatial CEST contrasts. Impact: We evaluated the effectiveness of using the field map generated by the Z-spectra to achieve the distortion self-correction for single-shot CEST-EPI. Results showed that DISC retrospectively and effectively corrected geometric distortion in CEST-EPI without acquiring an additional field map. |
| 4480.
 | 156 | An efficient CEST workflow using joint optimization of sampling, reconstruction and quantification Chuyu Liu1, Zhongsen Li1, and Xiaolei Song1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China Keywords: CEST / APT / NOE, CEST & MT Motivation: As an exciting ‘label-free' molecular imaging technique, CEST workflow is always time-consuming, because of the seconds-long TR and multiple frequency repetitions in acquisition, the iteration in reconstruction, and the pixel-by-pixel in B0 correction and quantification. Goal(s): To achieve rapid and high-quality sampling, reconstruction and quantification of CEST-MRI. Approach: We constructed a data-driven CEST framework, by joint optimization of k-space sampling, reconstruction and quantification. Results: Retrospective experiments on human brain demonstrated the feasibility of combination with acceleration techniques including parallel imaging, compress sensing or deep learning, allowing 6X under-sampling rate and reconstruction of high-quality contrast maps in one second. Impact: A data-driven CEST
framework enabled joint optimization of k-space sampling,reconstruction and
quantification. Retrospective experiments demonstrated that the the framework allows 6X under-sampling rate
and reconstruction of high-quality contrast maps in one second. This one-stop workflow may facilitate more clinical needs. |
| 4481.
 | 157 | Motion-induced B1+-changes in dynamic glucose enhanced (DGE) MRI and how to remedy them. Patrick M. Lehmann1, Emil Ljungberg1,2, Karin Markenroth Bloch3, Nirbhay N. Yadav4,5, Ronnie Wirestam1, Pia C. Sundgren3,6,7, Peter C. van Zijl4,5, and Linda Knutsson1,5,8
1Department of Medical Radiation Physics, Lund University, Lund, Sweden, 2Department of Neuroimaging, King’s College London, London, United Kingdom, 3Lund University Bioimaging Centre, Lund University, Lund, Sweden, 4Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, 5F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, 6Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden, 7Department of Radiology, Lund University, Lund, Sweden, 8Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States Keywords: CEST / APT / NOE, Brain, Motion Correction Motivation: Motion-induced B1+-changes at the voxel level result in erroneous dynamic glucose enhanced (DGE) MRI effects. Goal(s): To investigate effects of motion-induced B1+-changes on DGE MRI and to address removing them. Approach: A volunteer changed head positions, and voxel-based B1+ was measured pre- and post-motion. Z-spectra with and without D-glucose infusion were simulated, with and without the measured B1+-changes. Results: Slight motion-induced B1+-alterations lead to pseudo-CEST effects comparable to DGE effects. These can be removed by acquiring a full Z-spectrum and using the asymmetry of the glucoCEST signal relative to the water frequency to assess the DGE signal changes. Impact: Motion-induced B1+-changes affect DGE signals, thus
causing pseudo-CEST effects that complicate clinical interpretation. These
effects can be overcome by acquiring a full Z-spectrum and exploiting the
asymmetry of the glucoCEST signal changes relative to the water frequency. |
| 4482.
 | 158 | A scanner-inline software for performing permuted random forest for CEST frequency importance analysis Rui Guo1, Chuyu Liu1, and Xiaolei Song1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China Keywords: CEST / APT / NOE, CEST & MT Motivation: CEST quantitation typically relies on model-based fitting and always performs off-scanner. Besides, model-based fitting requires collection a number of saturation frequencies, hindering the clinical applications. Goal(s): To facilitate CEST applications by implementing a scanner-inline software through model-free analysis. Approach: We implemented CEST frequency importance analysis on Philips pride platform, which could rank the acquired frequencies according their contribution to lesion classification, using a permuted random forest algorithm. Results: Without specific requirement for sampled frequencies, this software allows researchers to extract frequency importance feature, either between lesion voxels and control ones, or between two different time points or different subjects. Impact: Compared with the conventional analysis based on fitting line-shape of the spectra, this PRF method does not have specific requirement for sampled frequencies on spectra, but fully explore all acquired ones, which is user-friendly and facilitate CEST applications. |
| 4483.
 | 159 | Analytical solution of the Bloch-McConnell equations for steady-state CEST Z-spectra Mehran Shaghaghi1 and Kejia Cai1
1Radiology, University of Illinois - Chicago, Chicago, IL, United States Keywords: CEST / APT / NOE, CEST & MT, Exchange rate quantification Motivation: Fitting CEST-MRI spectra using numerical methods is currently a time-consuming process, involving various approximations for initial parameters to expedite the process. Goal(s): We aimed to derive the exact analytical expression for CEST Z-spectra of a two-pool exchange system. Approach: We directly solved the Bloch-McConnell differential equations in matrix form for a two-pool exchange system to determine water magnetization under a steady-state saturation over the entire Z-spectrum. Results: The analytical solution accurately reproduces spectra obtained through numerical methods. It allows fitting for physical parameters of the exchange system (like the exchange rate) as demonstrated by fitting simulated CEST spectra. Impact: The analytical solution significantly reduces fitting time compared to the numerical methods used for fitting CEST Z-spectra. This solution has been demonstrated for the determination of physical parameters in the exchange system with fewer assumptions. |